Computational Economics

Abstract This study examines the presence, prevalence, and negative polarity of one-time reviewers compared to those who have left multiple reviews across all categories, based on an analysis of 571,544,746 Amazon product reviews. Since sellers and consumers may be interested in specific products relevant to their business or purchasing interests within a category rather than across all categorie…

Abstract Accurate and timely assessments of economic indicators are essential to provide an early analysis of the economic situations. Therefore, forecasting and nowcasting applications with the Artificial Intelligence (AI) and Machine Learning (ML) technologies, which are offering enhanced accuracy and timeliness in predictions, have been widely used. The emerging chatbot technologies provide ne…

Abstract In this paper, we introduce the Bayesian Gibbs Slice Sampler (BGSS), a novel MCMC algorithm where Bayesian inference is employed to estimate the slice width on each iteration, as well as a conditionally univariate factorization of the parameter space that confer a substantial efficiency to the exploration process. This efficiency can be further improved by using an initial QR decompositi…

This research presents a regime-aware hybrid forecasting framework for the Bitcoin market’s nonlinear, nonstationary and regime-switching behavior. The architecture integrates econometric models, neural forecasting and meta-learning, unified under a regime-detection mechanism using probabilistic inference. Central to the approach is a Hidden Markov Model (HMM) trained on log returns, which infers…

Financial series change their behavior over time and contain noise at many scales, which weakens standard linear forecasts. We present WaveESN–RegimeMLP, a modular pipeline that combines (i) wavelet-based multiscale features, (ii) a reservoir network with an elastic-net readout, (iii) a hidden-state model that detects market regimes from residuals, and (iv) genetic search for hyperparameters. Eva…